Smart Stormwater and Wastewater:
Combined Sewer Overflows (CSOs) and Sanitary Sewer Overflows (SSOs) pose a significant threat to the environment and public health. Determining when and where they occur – as well as their duration and volume – are critical information for operators to make informed and proactive decisions to mitigate sewer overflows.
Our research focuses on (1) developing novel approaches to identify and locate sewer operational problems in real-time, thereby helping sewer managers and operators to make more informed and proactive decisions to prevent (e.g., removing blockages) sewer overflows; and (2) bridging big data computational algorithms (artificial intelligence [AI]) with physics-based models for drastically reducing the period of machine learning and hence accelerating the availability of AI technology for mitigation of sewer overflows.
A simulation with our software ITM
Another simulation with ITM
Schematic of our deep learning model for predicting sewer overflows.
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